Search results
Results from the WOW.Com Content Network
Level of measurement or scale of measure is a classification that describes the nature of information within the values assigned to variables. [1] Psychologist Stanley Smith Stevens developed the best-known classification with four levels, or scales, of measurement: nominal , ordinal , interval , and ratio .
One of his most influential contributions was his definition of a measurement scale defined by four types: Nominal, Ordinal, Interval, and Ratio. (see Level of measurement) [11] He is the author of the operational theory of measurement, which “...in the broadest sense, is defined as the assignment of numerals to objects or events according to ...
Validity of a scale or test is ability of the instrument to measure what it purports to measure. [3] Construct validity, Content Validity, and Criterion Validity are types of validity. Construct validity is estimated by convergent and discriminant validity and factor analysis.
The level of measurement is a taxonomy for the methodological character of a comparison. For example, two states of a property may be compared by ratio, difference, or ordinal preference. The type is commonly not explicitly expressed, but implicit in the definition of a measurement procedure.
The Guttman scale is related to Rasch measurement; specifically, Rasch models bring the Guttman approach within a probabilistic framework. Constant sum scale – a respondent is given a constant sum of money, script, credits, or points and asked to allocate these to various items (example : If one had 100 Yen to spend on food products, how much ...
The definition of measurement in the social sciences has a long history. A current widespread definition, proposed by Stanley Smith Stevens, is that measurement is "the assignment of numerals to objects or events according to some rule." This definition was introduced in a 1946 Science article in which Stevens proposed four levels of ...
The concept of data type is similar to the concept of level of measurement, but more specific. For example, count data requires a different distribution (e.g. a Poisson distribution or binomial distribution) than non-negative real-valued data require, but both fall under the same level of measurement (a ratio scale).
"Statistics is both the science of uncertainty and the technology of extracting information from data." - featured in the International Encyclopedia of Statistical Science. [5] Statistics is the discipline that deals with data, facts and figures with which meaningful information is inferred. Data may represent a numerical value, in form of ...